Pharma · Analytics ·

Pharmacovigilance & safety signals

Detect pharmacovigilance signals, track adverse-event reports and regulatory deadlines.

Illustrative preview of the SAP Analytics Cloud dashboard Pharmacovigilance & safety signals for the Pharma industry: metrics Serious adverse events, Signals detected, Reporting lead time, Cases processed, analyzed by Product, Severity, Country.
Illustrative preview of a possible rendering in SAC. Brand colors and structure; synthetic figures.

KPIs included

  • Serious adverse events
  • Signals detected
  • Reporting lead time
  • Cases processed

Analysis dimensions

  • Product
  • Severity
  • Country

About this template

Detect pharmacovigilance signals, track adverse-event reports and regulatory deadlines. Designed for teams in the Pharma industry, the model pre-wires 4 key metrics — including Serious adverse events and Signals detected — analyzable across 3 analysis axes (Product, Severity, Country). You start from an already-bounded base (units, aggregations and business labels defined) rather than a blank sheet.

After downloading, import Pharmacovigilance & safety signals into SAC Modeler (Files → New Model → Import data from a file), map the 3 dimensions and 4 measures, then build your Story. The provided dataset contains 720 to 960 rows with realistic values for the Pharma industry, available as .xlsx (multi-sheet workbook), .csv (flat table) and .package (ZIP bundle with model.json, data.csv and README).

FAQ

What is the "Pharmacovigilance & safety signals" template for?

It provides a ready-to-use SAC structure to drive analytics in the Pharma industry. The standard business KPIs and dimensions are already defined, saving you the modeling phase.

Which KPIs are included?

The template includes 4 metrics: Serious adverse events, Signals detected, Reporting lead time, Cases processed. Each is computed across the dimensions Product, Severity, Country.

How do I import it into SAP Analytics Cloud?

Download the .csv or .xlsx format, then in SAC: Files → New Model → Import data from a file. Map the columns (Dimensions then Measures), validate the types and build your Story. Allow 5 to 10 minutes for an operational model.